Future wireless systems require efficient utilization of the radio frequency spectrum in order to increase the data rate achievable within a given transmission bandwidth. This can be accomplished by employing multiple transmit and receive antennas combined with signal processing. A number of recently developed techniques and emerging standards are based on employing multiple antennas at a base station to improve the reliability of data communication over wireless media without compromising the effective data rate of the wireless systems. So called space-time block-codes (STBCs) are used to this end. Specifically, recent advances in wireless communications have demonstrated that by jointly encoding symbols over time and transmit antennas at a base station, one can obtain reliability (diversity) benefits as well as increases in the effective data rate from the base station to each user. These multiplexing (throughput) gain and diversity benefits depend on the space-time coding techniques employed at the base station. The multiplexing gains and diversity benefits are also inherently dependent on the number of transmit and receive antennas in the system being deployed, in the sense that they are fundamentally limited by the multiplexing-diversity trade-offs curves that are dictated by the number of transmit and the number of receive antennas in the system.
For high data rates and wideband transmission the use of OFDM makes the equalizer unnecessary. With multilevel modems, coded modulation systems can easily be designed by use of an outer binary code, e.g., a convolutional code and an interleaver in a so called bit-interleaved coded modulation (BICM) system. One such class of systems employing BICM are MIMO/OFDM/BICM/ID systems. Such systems can also employ an inner orthogonal or quasi-orthogonal space-time block code, although typically they will not. Also, the transmit antennas need not be collocated, although, typically they are collocated.
A number of receiver structures exist as options for transmission systems. Many of these designs include an inner-outer decoder structure, whereby the outer decoder is optimally selected. The designs include iterative decoding (ID) receivers with a MAP-based inner decoder, ID systems with a MaxLogMAP-based inner decoder, receivers using QRD/M-Algorithm based inner decoder, MMSE-based inner decoders, tree-search based inner decoders based on conventional SOMA, on SOMA versions with tree reordering, and on forward-backward SOMA versions with tree ordering.
ID receivers that have a MAP-based inner decoder use the optimum inner decoder and have the optimum bit-error-rate performance among all inner/outer decoder structures. However, the MAP-based inner decoder becomes computationally intractable as the number of transmit antennas (which equals the number of QAM symbols that need to be jointly resolved), referred to herein as N, and the number of bits represented by each QAM symbol, referred to herein as B, increase.
ID systems with a MaxLogMAP-based inner decoder have less complexity than the MAP-based system and are asymptotically (high SNR) optimal in that they have near optimum bit-error-rate performance at high SNR. However, the MaxLogMAP-based inner decoder also becomes computationally intractable as N and B increase.
Systems with receivers using QRD/M-Algorithm based inner decoder also use a variant of the M-algorithm to produce hard bit estimates along with reliability information. They perform a limited tree-search whereby at every level of the tree only the M best candidates are kept and expanded through the next level in the tree. As a result, they can yield drastic reductions in complexity by proper choice of the M parameter, at a cost in bit-error-rate performance. These methods directly employ the “hard-output” M-algorithm, to generate hard-output estimates, and then employ the resulting M full-length candidates to obtain soft information. However, to generate soft information for any bit location, both values of the bit must be available in the pool of the remaining M candidates. As a result, when one of the bit-values is missing for a given bit location in the set M full-length candidates, these methods resort to heuristic (and inferior) softify-ing techniques to generate soft output for each bit. Also, these methods do not exploit iterative decoding.
MMSE-based inner decoders have much lower complexity but suffer in bit-error-rate performance, especially, at higher outer-code rates.
Systems employing a tree search based on conventional SOMA where reliability values are calculated recursively in the forward direction only will sometimes yield reliability values which are not calculated relative to the globally best sequence estimating the MAP or MLD output sequence; these typically also use a large number of early terminated paths to collect soft output at the intermediate levels in the tree.
Schemes involving forward-backward SOMA versions with tree reordering correspond to the best soft-output algorithms subject to the constraint that the survivor list at each stage consists of the paths with the best set of metrics. Some proposed algorithms do not necessarily include all the paths with the best metrics and can outperform the forward-backward SOMAs by providing bit log-likelihood ratios (bit-LLRs), i.e., soft-output information, based on longer sequences.
Note also that there exist many other inner decoder structures, including spherical decoders, soft-output Viterbi-algorithm (SOVA) based inner-decoders, etc.